Description:
％ Train a two layer neural network with the Levenberg-Marquardt
％ method.
％
％ If desired, it is possible to use regularization by
％ weight decay. Also pruned (ie. not fully connected) networks can
％ be trained.
％
％ Given a set of corresponding input-output pairs and an initial
％ network,
％ [W1,W2,critvec,iteration,lambda]=marq(NetDef,W1,W2,PHI,Y,trparms)
％ trains the network with the Levenberg-Marquardt method.
％
％ The activation functions can be either linear or tanh. The
％ network architecture is defined by the matrix NetDef which
％ has two rows. The first row specifies the hidden layer and the
％ second row specifies the output layer.- Train a two layer neural network with the Levenberg-Marquardt method. If desired, it is possible to use regularization by weight decay. Also pruned (ie. not fully connected) networks can be trained. Given a set of corresponding input-output pairs and an initial network, [W1, W2, critvec, iteration, lambda] = marq (NetDef, W1, W2, PHI, Y, trparms) trains the network with the Levenberg-Marquardt method . The activation functions can be either linear or tanh. The network architecture is defined by the matrix NetDef which has two rows. The first row specifies the hidden layer and the second row specifies the output layer. Platform: |
Size: 3072 |
Author:张镇 |
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Description: The economic load dispatch plays an important role in the operation of power system,
and several models by using different techniques have been used to solve these problems.
Several traditional approaches, like lambda-iteration and gradient method are utilized to find out
the optimal solution of non-linear problem. More recently, the soft computing techniques have
received more attention and were used in a number of successful and practical applications. The
purpose of this work is to find out the advantages of application of the evolutionary computing
technique and Particle Swarm Optimization (PSO) in particular to the economic load dispatch
problem. Here, an attempt has been made to find out the minimum cost by using PSO using the
data of three and six generating units Platform: |
Size: 542720 |
Author:amijeet |
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Description: This program finds economic distribution of power by the units to meet the given load. Newton Method is adapted in the program. Lambda value is assumed first and improved after each iteration. The updated value of lambda is
-> New Lambda Old Lambda +[ (demand -Sum of units)/Sum(1/coefficient of P in question)]-This program finds economic distribution of power by the units to meet the given load. Newton Method is adapted in the program. Lambda value is assumed first and improved after each iteration. The updated value of lambda is
-> New Lambda Old Lambda+[ (demand-Sum of units)/Sum(1/coefficient of P in question)] Platform: |
Size: 2048 |
Author:靳绍珍 |
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Description: By using simple lambda iteration technique solve the economic dispatch problem, give the data for any number of units and respective loss matrix B Platform: |
Size: 2048 |
Author:md adil |
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Search - lambda iteration